APACPH Poster - Bibliometric

1 Preamble

2 Analysis

Code

pacman::p_load(tidyverse, 
               bibliometrix,
               janitor,       # data cleaning
               stringr)

bibds_pm <- convert2df(file = "23-05-22 scopus search.bib",
                       dbsource = "scopus",
                       format = "bibtex")

Converting your scopus collection into a bibliographic dataframe


Warning:
In your file, some mandatory metadata are missing. Bibliometrix functions may not work properly!

Please, take a look at the vignettes:
- 'Data Importing and Converting' (https://www.bibliometrix.org/vignettes/Data-Importing-and-Converting.html)
- 'A brief introduction to bibliometrix' (https://www.bibliometrix.org/vignettes/Introduction_to_bibliometrix.html)


Missing fields:  CR 
Done!


Generating affiliation field tag AU_UN from C1:  Done!

Code

missingData(bibds_pm)

$allTags
                               cols missing_counts missing_pct
AU                               AU              0        0.00
DE                               DE             16       10.88
ID                               ID             11        7.48
C1                               C1              2        1.36
JI                               JI              0        0.00
AB                               AB              2        1.36
coden                         coden             73       49.66
RP                               RP             19       12.93
DI                               DI              9        6.12
SN                               SN              0        0.00
SO                               SO              0        0.00
LA                               LA              0        0.00
TC                               TC              0        0.00
PN                               PN             13        8.84
PP                               PP             26       17.69
pmid                           pmid             42       28.57
publication_stage publication_stage              0        0.00
PU                               PU             37       25.17
DB                               DB              0        0.00
TI                               TI              0        0.00
DT                               DT              0        0.00
url                             url              0        0.00
VL                               VL              1        0.68
PY                               PY              0        0.00
J9                               J9              0        0.00
CR                               CR            147      100.00
AU_UN                         AU_UN              3        2.04
AU1_UN                       AU1_UN              0        0.00
AU_UN_NR                   AU_UN_NR            147      100.00
SR_FULL                     SR_FULL              0        0.00
SR                               SR              0        0.00
                              status
AU                         Excellent
DE                        Acceptable
ID                              Good
C1                              Good
JI                         Excellent
AB                              Good
coden                           Poor
RP                        Acceptable
DI                              Good
SN                         Excellent
SO                         Excellent
LA                         Excellent
TC                         Excellent
PN                              Good
PP                        Acceptable
pmid                            Poor
publication_stage          Excellent
PU                              Poor
DB                         Excellent
TI                         Excellent
DT                         Excellent
url                        Excellent
VL                              Good
PY                         Excellent
J9                         Excellent
CR                Completely missing
AU_UN                           Good
AU1_UN                     Excellent
AU_UN_NR          Completely missing
SR_FULL                    Excellent
SR                         Excellent

$mandatoryTags
   tag                description missing_counts missing_pct             status
1   AU                     Author              0        0.00          Excellent
2   DT              Document Type              0        0.00          Excellent
3   SO                    Journal              0        0.00          Excellent
4   LA                   Language              0        0.00          Excellent
5   PY           Publication Year              0        0.00          Excellent
6   TI                      Title              0        0.00          Excellent
7   TC             Total Citation              0        0.00          Excellent
8   AB                   Abstract              2        1.36               Good
9   C1                Affiliation              2        1.36               Good
10  DI                        DOI              9        6.12               Good
11  ID              Keywords Plus             11        7.48               Good
12  DE                   Keywords             16       10.88         Acceptable
13  RP       Corresponding Author             19       12.93         Acceptable
14  CR           Cited References            147      100.00 Completely missing
15  NR Number of Cited References            147      100.00 Completely missing
16  WC         Science Categories            147      100.00 Completely missing

Code

bibres <- biblioAnalysis(bibds_pm, sep = ";")

2.1 General Information

Code

bibres_summary <- summary(bibres, k = 25)

MAIN INFORMATION ABOUT DATA

 Timespan                              1995 : 2022 
 Sources (Journals, Books, etc)        99 
 Documents                             147 
 Annual Growth Rate %                  12.13 
 Document Average Age                  8.2 
 Average citations per doc             40.07 
 Average citations per year per doc    3.215 
 References                            1 
 
DOCUMENT TYPES                     
 article              135 
 article article      1 
 review               11 
 
DOCUMENT CONTENTS
 Keywords Plus (ID)                    844 
 Author's Keywords (DE)                242 
 
AUTHORS
 Authors                               646 
 Author Appearances                    713 
 Authors of single-authored docs       5 
 
AUTHORS COLLABORATION
 Single-authored docs                  5 
 Documents per Author                  0.228 
 Co-Authors per Doc                    4.85 
 International co-authorships %        17.69 
 

Annual Scientific Production

 Year    Articles
    1995        1
    1996        1
    1998        2
    1999        1
    2000        2
    2001        2
    2002        1
    2003        2
    2004        4
    2005        5
    2006        1
    2007        1
    2008        3
    2009        7
    2010        4
    2011        3
    2012        5
    2013        5
    2014        5
    2015        8
    2016        4
    2017       11
    2018        9
    2019       17
    2020       11
    2021       10
    2022       22

Annual Percentage Growth Rate 12.13 


Most Productive Authors

       Authors        Articles     Authors        Articles Fractionalized
1  GRABOWSKA-FUDALA B        4 BYEON H                              1.000
2  JARACZ K                  4 CAMAK DJ                             1.000
3  VAN DEN BOS GAM           4 DEVI B                               1.000
4  GÓRNA K                   3 GREEN T                              1.000
5  KOZUBSKI W                3 JIANG Y                              1.000
6  POST MWM                  3 NA NA                                1.000
7  RAHMAN MM                 3 ZHU W                                1.000
8  VISSER-MEILY JMA          3 GRABOWSKA-FUDALA B                   0.893
9  AKOSILE CO                2 JARACZ K                             0.893
10 ALVARO R                  2 BLAKE H                              0.833
11 AMR M                     2 LINCOLN NB                           0.833
12 ASANO H                   2 FADILAH N                            0.750
13 AŞIRET GD                 2 KOZUBSKI W                           0.750
14 AUSILI D                  2 RAHARIYANI LD                        0.750
15 BLAKE H                   2 VAN DEN BOS GAM                      0.733
16 BROUWER WBF               2 AŞIRET GD                            0.700
17 CARO CC                   2 KAPUCU S                             0.700
18 CHEN YJ                   2 ASANO H                              0.667
19 CHOI-KWON S               2 MORIMOTO T                           0.667
20 COSTA JD                  2 POST MWM                             0.667
21 DA CRUZ DMC               2 SCHREINER AS                         0.667
22 DE ARAUJO TL              2 VISSER-MEILY JMA                     0.667
23 DESROSIERS J              2 DESROSIERS J                         0.583
24 EL-MONSHED AH             2 GÓRNA K                              0.560
25 ELSHEIKH MA               2 CARO CC                              0.533


Top manuscripts per citations

                                   Paper                                         DOI  TC TCperYear   NTC
1  ANDERSON CS, 1995, STROKE                      10.1161/01.STR.26.5.843            433     14.93 1.000
2  MCCULLAGH E, 2005, STROKE                      10.1161/01.STR.0000181755.23914.53 312     16.42 2.229
3  BHAKTA BB, 2000, J NEUROL NEUROSURG PSYCHIATRY 10.1136/jnnp.69.2.217              277     11.54 1.776
4  SCHOLTE OP REIMER WJM, 1998, STROKE            10.1161/01.str.29.8.1605           233      8.96 1.926
5  ELMSTÅHL S, 1996, ARCH PHYS MED REHABIL        10.1016/S0003-9993(96)90164-1      231      8.25 1.000
6  BUGGE C, 1999, STROKE                          10.1161/01.STR.30.8.1517           209      8.36 1.000
7  RIGBY H, 2009, INT J STROKE                    10.1111/j.1747-4949.2009.00289.x   208     13.87 3.324
8  MORIMOTO T, 2003, AGE AGEING                   10.1093/ageing/32.2.218            208      9.90 1.373
9  ZOROWITZ RD, 2013, NEUROLOGY                   10.1212/wnl.0b013e3182764c86       182     16.55 2.791
10 VAN EXEL NJA, 2004, CLIN REHABIL               10.1191/0269215504cr723oa          169      8.45 1.641
11 VAN EXEL NJA, 2005, CEREBROVASC DIS            10.1159/000081906                  134      7.05 0.957
12 VISSER-MEILY JMA, 2004, CLIN REHABIL           10.1191/0269215504cr776oa          131      6.55 1.272
13 HALEY WE, 2010, STROKE                         10.1161/STROKEAHA.109.568279       124      8.86 1.722
14 TOOTH L, 2005, BRAIN INJ                       10.1080/02699050500110785          110      5.79 0.786
15 CAMAK DJ, 2015, J CLIN NURS                    10.1111/jocn.12884                 107     11.89 2.503
16 CHOI-KWON S, 2005, ARCH PHYS MED REHABIL       10.1016/j.apmr.2004.09.013         105      5.53 0.750
17 DENNO MS, 2013, ARCH PHYS MED REHABIL          10.1016/j.apmr.2013.03.014         100      9.09 1.534
18 BLAKE H, 2003, CLIN REHABIL                    10.1191/0269215503cr613oa           95      4.52 0.627
19 PUCCIARELLI G, 2017, STROKE                    10.1161/STROKEAHA.116.014989        83     11.86 3.084
20 MCPHERSON CJ, 2010, REHABIL PSYCHOL            10.1037/a0019359                    83      5.93 1.153
21 KRUITHOF WJ, 2016, PATIENT EDUC COUNS          10.1016/j.pec.2016.04.007           79      9.88 3.398
22 JARACZ K, 2015, PATIENT EDUC COUNS             10.1016/j.pec.2015.04.008           72      8.00 1.684
23 HU P, 2018, MEDICINE                           10.1097/MD.0000000000012638         70     11.67 1.944
24 ILSE IB, 2008, DISABIL REHABIL                 10.1080/09638280701355645           65      4.06 1.523
25 RIGBY H, 2009, INT J STROKE-a                  10.1111/j.1747-4949.2009.00287.x    64      4.27 1.023


Corresponding Author's Countries

              Country Articles    Freq SCP MCP MCP_Ratio
1  USA                      17 0.13077  14   3     0.176
2  CHINA                    13 0.10000  11   2     0.154
3  NIGERIA                   8 0.06154   5   3     0.375
4  TURKEY                    8 0.06154   8   0     0.000
5  UNITED KINGDOM            8 0.06154   8   0     0.000
6  INDIA                     7 0.05385   6   1     0.143
7  IRAN                      7 0.05385   6   1     0.143
8  NETHERLANDS               7 0.05385   7   0     0.000
9  BRAZIL                    6 0.04615   4   2     0.333
10 KOREA                     6 0.04615   3   3     0.500
11 CANADA                    5 0.03846   5   0     0.000
12 JAPAN                     5 0.03846   3   2     0.400
13 THAILAND                  4 0.03077   3   1     0.250
14 AUSTRALIA                 2 0.01538   2   0     0.000
15 INDONESIA                 2 0.01538   2   0     0.000
16 ITALY                     2 0.01538   0   2     1.000
17 NORWAY                    2 0.01538   2   0     0.000
18 PAKISTAN                  2 0.01538   2   0     0.000
19 POLAND                    2 0.01538   2   0     0.000
20 SPAIN                     2 0.01538   2   0     0.000
21 SWEDEN                    2 0.01538   2   0     0.000
22 UGANDA                    2 0.01538   0   2     1.000
23 BENIN                     1 0.00769   1   0     0.000
24 DENMARK                   1 0.00769   1   0     0.000
25 DOMINICAN REPUBLIC        1 0.00769   0   1     1.000


SCP: Single Country Publications

MCP: Multiple Country Publications


Total Citations per Country

         Country      Total Citations Average Article Citations
1  USA                            745                     43.82
2  NETHERLANDS                    739                    105.57
3  UNITED KINGDOM                 603                     75.38
4  CANADA                         416                     83.20
5  DENMARK                        312                    312.00
6  JAPAN                          254                     50.80
7  CHINA                          239                     18.38
8  KOREA                          201                     33.50
9  NIGERIA                        149                     18.62
10 INDIA                          137                     19.57
11 ITALY                          136                     68.00
12 BRAZIL                         118                     19.67
13 AUSTRALIA                      111                     55.50
14 SPAIN                          100                     50.00
15 IRAN                            92                     13.14
16 SWEDEN                          80                     40.00
17 TURKEY                          58                      7.25
18 THAILAND                        50                     12.50
19 NORWAY                          49                     24.50
20 GEORGIA                         32                     32.00
21 POLAND                          32                     16.00
22 ISRAEL                          31                     31.00
23 HONG KONG                       23                     23.00
24 FRANCE                          18                     18.00
25 BENIN                           16                     16.00


Most Relevant Sources

                                                                       Sources        Articles
1  STROKE                                                                                    8
2  CEREBROVASCULAR DISEASES                                                                  5
3  CLINICAL REHABILITATION                                                                   5
4  TOPICS IN STROKE REHABILITATION                                                           5
5  ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION                                          4
6  DISABILITY AND REHABILITATION                                                             4
7  REHABILITATION NURSING                                                                    4
8  ANNALS OF INDIAN ACADEMY OF NEUROLOGY                                                     3
9  BMJ OPEN                                                                                  3
10 INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH                         3
11 JOURNAL OF NEUROSCIENCE NURSING                                                           3
12 MEDICINE (UNITED STATES)                                                                  3
13 ANNALS OF PHYSICAL AND REHABILITATION MEDICINE                                            2
14 BRAIN INJURY                                                                              2
15 DISABILITY AND HEALTH JOURNAL                                                             2
16 HEALTH AND QUALITY OF LIFE OUTCOMES                                                       2
17 HEALTH AND SOCIAL CARE IN THE COMMUNITY                                                   2
18 INTERNATIONAL JOURNAL OF STROKE                                                           2
19 JOURNAL OF CLINICAL NURSING                                                               2
20 JOURNAL OF STROKE AND CEREBROVASCULAR DISEASES                                            2
21 PATIENT EDUCATION AND COUNSELING                                                          2
22 WORKING WITH OLDER PEOPLE                                                                 2
23 ACTA CLINICA CROATICA                                                                     1
24 ACTA MEDICA (HRADEC KRÁLOVÉ) / UNIVERSITAS CAROLINA FACULTAS MEDICA HRADEC KRÁLOVÉ        1
25 ACTA NEUROLOGICA BELGICA                                                                  1


Most Relevant Keywords

    Author Keywords (DE)      Articles   Keywords-Plus (ID)     Articles
1  STROKE                          101 FEMALE                        189
2  CAREGIVERS                       41 MALE                          189
3  BURDEN                           34 AGED                          168
4  CAREGIVER BURDEN                 30 ADULT                         144
5  CAREGIVER                        28 HUMAN                         136
6  DEPRESSION                       25 MIDDLE AGED                   128
7  QUALITY OF LIFE                  25 STROKE                        126
8  REHABILITATION                   11 CAREGIVER                     108
9  ANXIETY                           9 CEREBROVASCULAR ACCIDENT      106
10 NURSING                           8 ARTICLE                       100
11 STROKE SURVIVORS                  8 QUALITY OF LIFE                99
12 ACTIVITIES OF DAILY LIVING        7 HUMANS                         94
13 CAREGIVING                        7 CAREGIVER BURDEN               92
14 SOCIAL SUPPORT                    7 CAREGIVERS                     91
15 STRAIN                            7 MAJOR CLINICAL STUDY           68
16 FAMILY CAREGIVER                  5 DEPRESSION                     65
17 INFORMAL CAREGIVERS               5 COST OF ILLNESS                53
18 STRESS                            5 PSYCHOLOGICAL                  51
19 STROKE SURVIVOR                   5 CONTROLLED STUDY               46
20 FAMILY CAREGIVERS                 4 PSYCHOLOGY                     45
21 FATIGUE                           4 STROKE REHABILITATION          41
22 QUALITATIVE                       4 SURVIVOR                       35
23 STROKE OUTCOME                    4 CROSS-SECTIONAL STUDY          34
24 BURDEN OF CARE                    3 STROKE PATIENT                 33
25 CARE BURDEN                       3 FAMILY                         32

Code

#plot(bibres, k = 25)

2.1.1 Publication per year

Code

tibble(Article = rownames(bibds_pm),
       Year = bibds_pm$PY) %>% 
  group_by(Year) %>% 
  summarise(n = n()) %>% 
  ggplot(aes(x = Year, y = n)) +
  geom_area(alpha = .2) +
  geom_point() +
  geom_line() +
  scale_y_continuous(breaks = seq(0,28,4)) +
  scale_x_continuous(breaks = seq(1987,2023,4)) +
  coord_cartesian(ylim = c(0,28)) +
  labs(x = "Year", y = "Number of Publication") +
  theme_bw()

2.2 Language

Code

bib_lang <- bibds_pm %>% 
  group_by(LA) %>% 
  summarise(n = n()) %>% 
  mutate(percent = n / sum(n) * 100,
         percent = round(percent, 1)) %>% 
  arrange(desc(n))

bib_lang

2.3 Countries

Code

bibres_countrylist <- bibres$Countries

bibres_countrytable <- tibble(Rank = seq_along(bibres_countrylist),
                              Country = rownames(bibres_countrylist),
                              Np = as.integer(bibres_countrylist))

bibres_countrytable

Code

bibressum_countrytable <- tibble(Rank = 1:25,
                                 bibres_summary$TCperCountries) %>% 
  rename("Country" = "Country     ") %>% 
  mutate(Country = str_trim(Country),
         Country = fct_reorder(Country, Rank),
         `Total Citations` = as.integer(`Total Citations`),
         `Average Article Citations` = as.double(`Average Article Citations`),
         percent = `Total Citations` / sum(`Total Citations`) * 100,
         percent = round(percent,1)) %>% 
  inner_join(x = ., y = select(bibres_countrytable, Country, Np), 
             by = "Country") %>% 
  relocate(percent, .after = `Total Citations`)

bibressum_countrytable

Code

bib_concolab <- metaTagExtraction(bibds_pm, Field = "AU_CO", sep = ";")

bib_concolab_NetMatrix <- biblioNetwork(bib_concolab, analysis = "collaboration",
                                        network = "countries", sep = ";")

bib_concolab_Plot <- networkPlot(bib_concolab_NetMatrix,
                                 n = dim(bib_concolab_NetMatrix)[1],
                                 Title = "Country collaboration",
                                 type = "auto",
                                 size=20,
                                 size.cex=T,
                                 edgesize = 2,
                                 labelsize=1,
                                 #edges.min = 1,
                                 remove.isolates = T,
                                 community.repulsion = 0,
                                 cluster = "optimal"
                                 )

for collaboration network, using biblioshiny is nicer

2.4 Institution

Code

bibres_instlist <- bibres$Affiliations

bibres_insttable <- tibble(Rank = seq_along(bibres_instlist),
                           InstitutionAffiliation = rownames(bibres_instlist),
                           Np = as.integer(bibres_instlist)) %>% 
  mutate(InstitutionAffiliation = fct_reorder(InstitutionAffiliation, Rank))

bibres_insttable

Code

bib_educolab_NetMatrix <- biblioNetwork(bibds_pm, analysis = "collaboration",
                                       network = "universities", sep = ";")

bib_educolab_Plot <- networkPlot(bib_educolab_NetMatrix, 
                                 n = 100, 
                                 cluster = "optimal", 
                                 type = "auto",
                                 size.cex = F, 
                                 size = 3, 
                                 remove.multiple = F,
                                 labelsize=1, 
                                 alpha = .7, 
                                 edgesize = 1,
                                 edges.min = 2, 
                                 remove.isolates = T, 
                                 community.repulsion = 0,
                                 Title = "Institutions collaboration")

2.5 Journal

Code

bibres_sourcelist <- bibres$Sources

bibres_sourcetable <- tibble(Rank = seq_along(bibres_sourcelist),
                             SourceJournal = rownames(bibres_sourcelist),
                             Np = as.integer(bibres_sourcelist)) %>% 
  mutate(SourceJournal = fct_reorder(SourceJournal, Rank))

bibres_sourcetable

Code

bibres_sourcetablepercent <- bibres_sourcetable %>% 
  count(Np) %>% 
  mutate(percent = n / sum(n) * 100,
         percent = round(percent,1))

bibres_sourcetablepercent

Code

bib_bradford <- bradford(bibds_pm)

bib_bradfordtable <- bib_bradford$table %>% 
  select(Zone, Freq, Rank) %>% 
  tibble() %>% 
  group_by(Zone) %>% 
  summarise(nSO = n(),
            nArt = sum(Freq),
            RankRange = str_c(min(Rank), max(Rank), sep = "-")) %>% 
  mutate(percent = nArt / sum(nArt) * 100,
         percent = round(percent,1))

bib_bradfordtable

Code

# bib_CRSO <- metaTagExtraction(bibds_pm, Field = "CR_SO", sep = ";")
# bib_CRSO_NetMatrix <- biblioNetwork(bib_CRSO, analysis = "co-citation", 
#                                     network = "sources", sep = ";")
# bib_CRSO_Plot <- networkPlot(bib_CRSO_NetMatrix, n = 20, 
#                              Title = "Co-citation Network", type = "auto", 
#                              size.cex = T, size = 20, remove.multiple = F,
#                              labelsize = 1, edgesize = 5, edges.min = 5, alpha = 1)

co-citation network not available

2.6 Author

Code

bibds_noaufreq <- bibds_pm %>% 
  select(TI, AU, DT) %>% 
  tibble() %>% 
  mutate(no_auth = str_count(AU, pattern = ";") + 1) %>% 
  rename("paper" = "TI", "author" = "AU", "type" = "DT") %>% 
  group_by(no_auth, type) %>% 
  summarise(freq = n(), .groups = "drop") %>% 
  mutate(percent = freq / sum(freq) * 100,
         percent = round(percent,1))

bibds_noaufreq %>% 
  ggplot(aes(no_auth, freq)) + 
  geom_bar(stat = "identity") + 
  labs(x = "Number of Authors", y = "Frequency (Number of Articles)") + 
  scale_x_continuous(breaks = seq(-3,30,2)) +
  scale_y_continuous(breaks = seq(-2,40,4)) +
  theme_bw()

Code

bibres_aulist <- bibres$Authors

bibres_autable <- tibble(Rank = seq_along(bibres_aulist),
                         Author = rownames(bibres_aulist),
                         Np = as.integer(bibres_aulist)) %>% 
  mutate(Author = fct_reorder(Author, Rank))

bibres_autable

Code

bibres_autablepercent <- bibres_autable %>% 
  count(Np) %>% 
  mutate(percent = n / sum(n) * 100,
         percent = round(percent,1))

bibres_autablepercent

Code

# bib_AuCoupling_NetMatrix <- biblioNetwork(bibds_pm, analysis = "coupling",
#                                           network = "authors", sep = ";")
# 
# bib_AuCoupling_Plot <- networkPlot(bib_AuCoupling_NetMatrix, n = 15, 
#                                    cluster = "optimal", type = "auto", 
#                                    size.cex = T, size = 20, remove.multiple = F,
#                                    Title = "Bibliographic coupling of the authors",
#                                    alpha = .7)

error also

2.7 Articles

Code

tibble(Title = bibds_pm$TI,
       Author = bibds_pm$AU,
       DOI = bibds_pm$DI,
       Citations = bibds_pm$TC) %>% 
  mutate(across(.cols = c(Title, Author), .fns = str_to_title)) %>% 
  arrange(desc(Citations)) %>% 
  head(n=10)

2.8 Keyword

Code

cbind(Rank = 1:25, bibres_summary$MostRelKeywords)

Code

bib_kwco_NetMatrix <- biblioNetwork(bibds_pm, analysis = "co-occurrences", 
                                     network = "keywords", sep = ";")

bib_kwco_Plot <- networkPlot(bib_kwco_NetMatrix, normalize = "association", 
                             n = 20, Title = "Keyword Co-occurences", 
                             cluster = "optimal", type = "fruchterman", 
                             size.cex = T, size = 20,  remove.multiple = F, 
                             edgesize = 7, labelsize = 3, label.cex = T, 
                             label.n = 20, edges.min = 10)

for co-occurence network, using biblioshiny is nicer

Code

bib_thememap <- thematicMap(bibds_pm, field = "DE", n = 200, minfreq = 20, 
                            stemming = F, size = .5, n.labels = 4, repel = T)

plot(bib_thememap$map)